Exploring Research Issues in Mining Medical Datasets

B. Bai, N. Mangathayaru, B. Rani
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引用次数: 2

Abstract

Mining medical datasets is a challenging problem before data mining researchers as these datasets have several hidden challenges compared to conventional datasets. Starting from the collection of samples through field experiments and clinical trials to performing classification, there are numerous challenges at every stage in the mining process. The preprocessing phase in the mining process itself is a challenging issue when, we work on medical datasets. The main contribution of this research includes the detailed survey carried out and brings out the discussion that is not initiated in research papers published in the fields of medical and health informatics. We made a sincere effort towards making this possible and aim to bring out the various research issues associated with the disease prediction from the perspective of data mining. We also discuss the nature of medical disease datasets before switching our attention towards prediction or classification.
探索挖掘医疗数据集的研究问题
对于数据挖掘研究人员来说,挖掘医疗数据集是一个具有挑战性的问题,因为与传统数据集相比,这些数据集存在一些隐藏的挑战。从通过现场实验和临床试验收集样品到进行分类,在挖掘过程的每个阶段都面临着许多挑战。当我们处理医疗数据集时,挖掘过程中的预处理阶段本身就是一个具有挑战性的问题。本研究的主要贡献包括进行了详细的调查,并提出了在医学和卫生信息学领域发表的研究论文中没有提出的讨论。我们为实现这一目标做出了真诚的努力,并旨在从数据挖掘的角度提出与疾病预测相关的各种研究问题。在将注意力转向预测或分类之前,我们还讨论了医学疾病数据集的性质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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